Machine learning-enhanced echocardiography for screening coronary artery disease.

ABSTRACT:

Background

Since myocardial work (MW) and left atrial strain are valuable for screening coronary artery disease (CAD), this study aimed to develop a novel CAD screening approach based on machine learning-enhanced echocardiography.

Methods

This prospective study used data from patients undergoing coronary angiography, in which the novel echocardiography features were extracted by a machine learning algorithm. A total of 818 patients were enrolled and randomly divided into training (80%) and testing (20%) groups. An additional 115 patients were also enrolled in the validation group.

Results

The superior diagnosis model of CAD was optimized using 59 echocardiographic features in a gradient-boosting classifier. This model showed that the value of the receiver operating ch

SUBMITTER: Guo Y 

PROVIDER: S-EPMC10176743 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature